fine-tuned-NLI-indonli_mnli_tydiqaid-nli-with-xlm-roberta-large – AI Model by muhammadravi251001 | AlphaNeural AI

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fine-tuned-NLI-indonli_mnli_tydiqaid-nli-with-xlm-roberta-large

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text-classification

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autotrain_compatible

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fine-tuned-NLI-indonli_mnli_tydiqaid-nli-with-xlm-roberta-large

This model is a fine-tuned version of xlm-roberta-large on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.5071
Accuracy: 0.8638
F1: 0.8643

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.4488	0.5	1612	0.4180	0.8433	0.8435
0.4256	1.0	3224	0.3902	0.8540	0.8550
0.3675	1.5	4836	0.3924	0.8590	0.8592
0.3625	2.0	6448	0.3671	0.8630	0.8633
0.2841	2.5	8060	0.4142	0.8630	0.8632
0.3103	3.0	9672	0.3989	0.8605	0.8612
0.2355	3.5	11284	0.4327	0.8652	0.8659
0.2478	4.0	12896	0.4083	0.8667	0.8669
0.211	4.5	14508	0.4466	0.8646	0.8645
0.2044	5.0	16120	0.4415	0.8653	0.8658
0.1546	5.5	17732	0.5071	0.8638	0.8643

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu117
Datasets 2.2.0
Tokenizers 0.13.2